from typing import Any
import httpx
from claude_agent_sdk import tool, create_sdk_mcp_server


# Define a tool: name, description, input schema, handler
@tool(
"get_temperature",
"Get the current temperature at a location",
{"latitude": float, "longitude": float},
)
async def get_temperature(args: dict[str, Any]) -> dict[str, Any]:
async with httpx.AsyncClient() as client:
response = await client.get(
"https://api.open-meteo.com/v1/forecast",
params={
"latitude": args["latitude"],
"longitude": args["longitude"],
"current": "temperature_2m",
"temperature_unit": "fahrenheit",
},
)
data = response.json()

# Return a content array - Claude sees this as the tool result
return {
"content": [
{
"type": "text",
"text": f"Temperature: {data['current']['temperature_2m']}°F",
}
]
}


# Wrap the tool in an in-process MCP server
weather_server = create_sdk_mcp_server(
name="weather",
version="1.0.0",
tools=[get_temperature],
)

import { tool, createSdkMcpServer } from "@anthropic-ai/claude-agent-sdk";
import { z } from "zod";

// Define a tool: name, description, input schema, handler
const getTemperature = tool(
"get_temperature",
"Get the current temperature at a location",
{
latitude: z.number().describe("Latitude coordinate"), // .describe() adds a field description Claude sees
longitude: z.number().describe("Longitude coordinate")
},
async (args) => {
// args is typed from the schema: { latitude: number; longitude: number }
const response = await fetch(
`https://api.open-meteo.com/v1/forecast?latitude=${args.latitude}&longitude=${args.longitude}&current=temperature_2m&temperature_unit=fahrenheit`
);
const data: any = await response.json();

// Return a content array - Claude sees this as the tool result
return {
content: [{ type: "text", text: `Temperature: ${data.current.temperature_2m}°F` }]
};
}
);

// Wrap the tool in an in-process MCP server
const weatherServer = createSdkMcpServer({
name: "weather",
version: "1.0.0",
tools: [getTemperature]
});

import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage


async def main():
options = ClaudeAgentOptions(
mcp_servers={"weather": weather_server},
allowed_tools=["mcp__weather__get_temperature"],
)

async for message in query(
prompt="What's the temperature in San Francisco?",
options=options,
):
# ResultMessage is the final message after all tool calls complete
if isinstance(message, ResultMessage) and message.subtype == "success":
print(message.result)


asyncio.run(main())

import { query } from "@anthropic-ai/claude-agent-sdk";

for await (const message of query({
prompt: "What's the temperature in San Francisco?",
options: {
mcpServers: { weather: weatherServer },
allowedTools: ["mcp__weather__get_temperature"]
}
})) {
// "result" is the final message after all tool calls complete
if (message.type === "result" && message.subtype === "success") {
console.log(message.result);
}
}

# Define a second tool for the same server
@tool(
"get_precipitation_chance",
"Get the hourly precipitation probability for a location. "
"Optionally pass 'hours' (1-24) to control how many hours to return.",
{"latitude": float, "longitude": float},
)
async def get_precipitation_chance(args: dict[str, Any]) -> dict[str, Any]:
# 'hours' isn't in the schema - read it with .get() to make it optional
hours = args.get("hours", 12)
async with httpx.AsyncClient() as client:
response = await client.get(
"https://api.open-meteo.com/v1/forecast",
params={
"latitude": args["latitude"],
"longitude": args["longitude"],
"hourly": "precipitation_probability",
"forecast_days": 1,
},
)
data = response.json()
chances = data["hourly"]["precipitation_probability"][:hours]

return {
"content": [
{
"type": "text",
"text": f"Next {hours} hours: {'%, '.join(map(str, chances))}%",
}
]
}


# Rebuild the server with both tools in the array
weather_server = create_sdk_mcp_server(
name="weather",
version="1.0.0",
tools=[get_temperature, get_precipitation_chance],
)

// Define a second tool for the same server
const getPrecipitationChance = tool(
"get_precipitation_chance",
"Get the hourly precipitation probability for a location",
{
latitude: z.number(),
longitude: z.number(),
hours: z
.number()
.int()
.min(1)
.max(24)
.default(12) // .default() makes the parameter optional
.describe("How many hours of forecast to return")
},
async (args) => {
const response = await fetch(
`https://api.open-meteo.com/v1/forecast?latitude=${args.latitude}&longitude=${args.longitude}&hourly=precipitation_probability&forecast_days=1`
);
const data: any = await response.json();
const chances = data.hourly.precipitation_probability.slice(0, args.hours);

return {
content: [{ type: "text", text: `Next ${args.hours} hours: ${chances.join("%, ")}%` }]
};
}
);

// Rebuild the server with both tools in the array
const weatherServer = createSdkMcpServer({
name: "weather",
version: "1.0.0",
tools: [getTemperature, getPrecipitationChance]
});

from claude_agent_sdk import tool, ToolAnnotations


@tool(
"get_temperature",
"Get the current temperature at a location",
{"latitude": float, "longitude": float},
annotations=ToolAnnotations(
readOnlyHint=True
),  # Lets Claude batch this with other read-only calls
)
async def get_temperature(args):
return {"content": [{"type": "text", "text": "..."}]}

import { tool } from "@anthropic-ai/claude-agent-sdk";
import { z } from "zod";

tool(
"get_temperature",
"Get the current temperature at a location",
{ latitude: z.number(), longitude: z.number() },
async (args) => ({ content: [{ type: "text", text: `...` }] }),
{ annotations: { readOnlyHint: true } } // Lets Claude batch this with other read-only calls
);

import json
import httpx
from typing import Any
from claude_agent_sdk import tool


@tool(
"fetch_data",
"Fetch data from an API",
{"endpoint": str},  # Simple schema
)
async def fetch_data(args: dict[str, Any]) -> dict[str, Any]:
try:
async with httpx.AsyncClient() as client:
response = await client.get(args["endpoint"])
if response.status_code != 200:
# Return the failure as a tool result so Claude can react to it.
# is_error marks this as a failed call rather than odd-looking data.
return {
"content": [
{
"type": "text",
"text": f"API error: {response.status_code} {response.reason_phrase}",
}
],
"is_error": True,
}

data = response.json()
return {"content": [{"type": "text", "text": json.dumps(data, indent=2)}]}
except Exception as e:
# Composes the message Claude reads. An uncaught exception would
# reach Claude as the raw str(e) with no context.
return {
"content": [{"type": "text", "text": f"Failed to fetch data: {str(e)}"}],
"is_error": True,
}

import { tool } from "@anthropic-ai/claude-agent-sdk";
import { z } from "zod";

tool(
"fetch_data",
"Fetch data from an API",
{
endpoint: z.string().url().describe("API endpoint URL")
},
async (args) => {
try {
const response = await fetch(args.endpoint);

if (!response.ok) {
// Return the failure as a tool result so Claude can react to it.
// isError marks this as a failed call rather than odd-looking data.
return {
content: [
{
type: "text",
text: `API error: ${response.status} ${response.statusText}`
}
],
isError: true
};
}

const data = await response.json();
return {
content: [
{
type: "text",
text: JSON.stringify(data, null, 2)
}
]
};
} catch (error) {
// Composes the message Claude reads. An uncaught throw would
// reach Claude as the raw error message with no context.
return {
content: [
{
type: "text",
text: `Failed to fetch data: ${error instanceof Error ? error.message : String(error)}`
}
],
isError: true
};
}
}
);

import base64
import httpx
from claude_agent_sdk import tool


# URL에서 이미지를 가져와 Claude에 반환하는 도구를 정의합니다
@tool("fetch_image", "Fetch an image from a URL and return it to Claude", {"url": str})
async def fetch_image(args):
async with httpx.AsyncClient() as client:  # 이미지 바이트를 가져옵니다
response = await client.get(args["url"])

return {
"content": [
{
"type": "image",
"data": base64.b64encode(response.content).decode(
"ascii"
),  # 원본 바이트를 base64로 인코딩합니다
"mimeType": response.headers.get(
"content-type", "image/png"
),  # 응답에서 MIME 유형을 읽습니다
}
]
}

import { tool } from "@anthropic-ai/claude-agent-sdk";
import { z } from "zod";

tool(
"fetch_image",
"Fetch an image from a URL and return it to Claude",
{
url: z.string().url()
},
async (args) => {
const response = await fetch(args.url); // 이미지 바이트를 가져옵니다
const buffer = Buffer.from(await response.arrayBuffer()); // base64 인코딩을 위해 버퍼로 읽습니다
const mimeType = response.headers.get("content-type") ?? "image/png";

return {
content: [
{
type: "image",
data: buffer.toString("base64"), // 원본 바이트를 base64로 인코딩합니다
mimeType
}
]
};
}
);

return {
content: [
{
type: "resource",
resource: {
uri: "file:///tmp/report.md", // Claude가 참조할 수 있는 레이블이며, SDK가 읽는 경로가 아닙니다
mimeType: "text/markdown",
text: "# Report\n..." // 실제 콘텐츠이며, 인라인입니다
}
}
]
};

return {
"content": [
{
"type": "resource",
"resource": {
"uri": "file:///tmp/report.md",  # Claude가 참조할 수 있는 레이블이며, SDK가 읽는 경로가 아닙니다
"mimeType": "text/markdown",
"text": "# Report\n...",  # 실제 콘텐츠이며, 인라인입니다
},
}
]
}

from typing import Any
from claude_agent_sdk import tool, create_sdk_mcp_server


# z.enum() in TypeScript becomes an "enum" constraint in JSON Schema.
# The dict schema has no equivalent, so full JSON Schema is required.
@tool(
"convert_units",
"Convert a value from one unit to another",
{
"type": "object",
"properties": {
"unit_type": {
"type": "string",
"enum": ["length", "temperature", "weight"],
"description": "Category of unit",
},
"from_unit": {
"type": "string",
"description": "Unit to convert from, e.g. kilometers, fahrenheit, pounds",
},
"to_unit": {"type": "string", "description": "Unit to convert to"},
"value": {"type": "number", "description": "Value to convert"},
},
"required": ["unit_type", "from_unit", "to_unit", "value"],
},
)
async def convert_units(args: dict[str, Any]) -> dict[str, Any]:
conversions = {
"length": {
"kilometers_to_miles": lambda v: v * 0.621371,
"miles_to_kilometers": lambda v: v * 1.60934,
"meters_to_feet": lambda v: v * 3.28084,
"feet_to_meters": lambda v: v * 0.3048,
},
"temperature": {
"celsius_to_fahrenheit": lambda v: (v * 9) / 5 + 32,
"fahrenheit_to_celsius": lambda v: (v - 32) * 5 / 9,
"celsius_to_kelvin": lambda v: v + 273.15,
"kelvin_to_celsius": lambda v: v - 273.15,
},
"weight": {
"kilograms_to_pounds": lambda v: v * 2.20462,
"pounds_to_kilograms": lambda v: v * 0.453592,
"grams_to_ounces": lambda v: v * 0.035274,
"ounces_to_grams": lambda v: v * 28.3495,
},
}

key = f"{args['from_unit']}_to_{args['to_unit']}"
fn = conversions.get(args["unit_type"], {}).get(key)

if not fn:
return {
"content": [
{
"type": "text",
"text": f"Unsupported conversion: {args['from_unit']} to {args['to_unit']}",
}
],
"is_error": True,
}

result = fn(args["value"])
return {
"content": [
{
"type": "text",
"text": f"{args['value']} {args['from_unit']} = {result:.4f} {args['to_unit']}",
}
]
}


converter_server = create_sdk_mcp_server(
name="converter",
version="1.0.0",
tools=[convert_units],
)

import { tool, createSdkMcpServer } from "@anthropic-ai/claude-agent-sdk";
import { z } from "zod";

const convert = tool(
"convert_units",
"Convert a value from one unit to another",
{
unit_type: z.enum(["length", "temperature", "weight"]).describe("Category of unit"),
from_unit: z
.string()
.describe("Unit to convert from, e.g. kilometers, fahrenheit, pounds"),
to_unit: z.string().describe("Unit to convert to"),
value: z.number().describe("Value to convert")
},
async (args) => {
type Conversions = Record<string, Record<string, (v: number) => number>>;

const conversions: Conversions = {
length: {
kilometers_to_miles: (v) => v * 0.621371,
miles_to_kilometers: (v) => v * 1.60934,
meters_to_feet: (v) => v * 3.28084,
feet_to_meters: (v) => v * 0.3048
},
temperature: {
celsius_to_fahrenheit: (v) => (v * 9) / 5 + 32,
fahrenheit_to_celsius: (v) => ((v - 32) * 5) / 9,
celsius_to_kelvin: (v) => v + 273.15,
kelvin_to_celsius: (v) => v - 273.15
},
weight: {
kilograms_to_pounds: (v) => v * 2.20462,
pounds_to_kilograms: (v) => v * 0.453592,
grams_to_ounces: (v) => v * 0.035274,
ounces_to_grams: (v) => v * 28.3495
}
};

const key = `${args.from_unit}_to_${args.to_unit}`;
const fn = conversions[args.unit_type]?.[key];

if (!fn) {
return {
content: [
{
type: "text",
text: `Unsupported conversion: ${args.from_unit} to ${args.to_unit}`
}
],
isError: true
};
}

const result = fn(args.value);
return {
content: [
{
type: "text",
text: `${args.value} ${args.from_unit} = ${result.toFixed(4)} ${args.to_unit}`
}
]
};
}
);

const converterServer = createSdkMcpServer({
name: "converter",
version: "1.0.0",
tools: [convert]
});

import asyncio
from claude_agent_sdk import (
query,
ClaudeAgentOptions,
ResultMessage,
AssistantMessage,
ToolUseBlock,
)


async def main():
options = ClaudeAgentOptions(
mcp_servers={"converter": converter_server},
allowed_tools=["mcp__converter__convert_units"],
)

prompts = [
"Convert 100 kilometers to miles.",
"What is 72°F in Celsius?",
"How many pounds is 5 kilograms?",
]

for prompt in prompts:
try:
async for message in query(prompt=prompt, options=options):
if isinstance(message, AssistantMessage):
for block in message.content:
if isinstance(block, ToolUseBlock):
print(f"[tool call] {block.name}({block.input})")
elif isinstance(message, ResultMessage) and message.subtype == "success":
print(f"Q: {prompt}\nA: {message.result}\n")
except Exception as error:
# A single-shot query() raises after yielding an error result. Only success
# results are printed above, so handle the failure here and continue with
# the next prompt.
print(f"Call failed: {error}")


asyncio.run(main())

import { query } from "@anthropic-ai/claude-agent-sdk";

const prompts = [
"Convert 100 kilometers to miles.",
"What is 72°F in Celsius?",
"How many pounds is 5 kilograms?"
];

for (const prompt of prompts) {
try {
for await (const message of query({
prompt,
options: {
mcpServers: { converter: converterServer },
allowedTools: ["mcp__converter__convert_units"]
}
})) {
if (message.type === "assistant") {
for (const block of message.message.content) {
if (block.type === "tool_use") {
console.log(`[tool call] ${block.name}`, block.input);
}
}
} else if (message.type === "result" && message.subtype === "success") {
console.log(`Q: ${prompt}\nA: ${message.result}\n`);
}
}
} catch (error) {
// A single-shot query() throws after yielding an error result. Only success
// results are logged above, so handle the failure here and continue with
// the next prompt.
console.error(`Call failed: ${error}`);
}
}